Scalable parallel OPTICS data clustering using graph algorithmic techniques

@article{Patwary2013ScalablePO,
  title={Scalable parallel OPTICS data clustering using graph algorithmic techniques},
  author={Md. Mostofa Ali Patwary and Diana Palsetia and Ankit Agrawal and Wei-keng Liao and Fredrik Manne and Alok N. Choudhary},
  journal={2013 SC - International Conference for High Performance Computing, Networking, Storage and Analysis (SC)},
  year={2013},
  pages={1-12}
}
OPTICS is a hierarchical density-based data clustering algorithm that discovers arbitrary-shaped clusters and eliminates noise using adjustable reachability distance thresholds. Parallelizing OPTICS is considered challenging as the algorithm exhibits a strongly sequential data access order. We present a scalable parallel OPTICS algorithm (Poptics) designed using graph algorithmic concepts. To break the data access sequentiality, POPTICS exploits the similarities between the OPTICS algorithm and… CONTINUE READING
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